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MME

MME is a comprehensive evaluation benchmark for multimodal large language models. It measures both perception and cognition abilities on a total of 14 subtasks, including existence, count, position, color, poster, celebrity, scene, landmark, artwork, OCR, commonsense reasoning, numerical calculation, text translation, and code reasoning.

Papers

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Showing 51–75 of 95 papers

TitleStatusHype
A Challenger to GPT-4V? Early Explorations of Gemini in Visual Expertise—0
AIDE: Agentically Improve Visual Language Model with Domain Experts—0
An LMM for Efficient Video Understanding via Reinforced Compression of Video Cubes—0
Apollo: An Exploration of Video Understanding in Large Multimodal Models—0
Benchmarking and In-depth Performance Study of Large Language Models on Habana Gaudi Processors—0
DAMRO: Dive into the Attention Mechanism of LVLM to Reduce Object Hallucination—0
Deep Learning for Hybrid 5G Services in Mobile Edge Computing Systems: Learn from a Digital Twin—0
Domain Adaptation via Minimax Entropy for Real/Bogus Classification of Astronomical Alerts—0
Don't Miss the Forest for the Trees: Attentional Vision Calibration for Large Vision Language Models—0
DrVideo: Document Retrieval Based Long Video Understanding—0
DynTok: Dynamic Compression of Visual Tokens for Efficient and Effective Video Understanding—0
EACO: Enhancing Alignment in Multimodal LLMs via Critical Observation—0
The economic value of empowering older patients transitioning from hospital to home: Evidence from the 'Your Care Needs You' intervention—0
Enhancing Instruction-Following Capability of Visual-Language Models by Reducing Image Redundancy—0
Enhancing the Spatial Awareness Capability of Multi-Modal Large Language Model—0
Enhancing Visual Reliance in Text Generation: A Bayesian Perspective on Mitigating Hallucination in Large Vision-Language Models—0
EvoMoE: Expert Evolution in Mixture of Experts for Multimodal Large Language Models—0
Fast or Slow? Integrating Fast Intuition and Deliberate Thinking for Enhancing Visual Question Answering—0
GFormer: Accelerating Large Language Models with Optimized Transformers on Gaudi Processors—0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
Improving LLM Video Understanding with 16 Frames Per Second—0
Language-Vision Planner and Executor for Text-to-Visual Reasoning—0
Learning Multilingual Meta-Embeddings for Code-Switching Named Entity Recognition—0
Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding—0
Machine Learning Methods for Inferring the Number of UAV Emitters via Massive MIMO Receive Array—0
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